Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging technique that utilizes magnetization to visualize soft tissue. The contrast of MRI is extraordinarily flexible; several physical tissue properties can be used as contrast parameters to extract anatomical, morphological and even functional information. Tissue properties may include but are not limited to relaxation parameters, diffusion perfusion, flow, etc. The achieved image contrast strongly depends on the used Magnetic Resonance (MR) protocols—a specific set of imaging parameters that describe data acquisition and image reconstruction. Such imaging protocols are the core element of a clinical MRI study. The optimal selection of an imaging protocol and associated imaging parameters strongly impacts the image quality and diagnostic performance of the MRI study and requires careful optimization to specific types of MRI scanners. Unfortunately, even small deviations from optimized MRI protocols may render an MR image as non-diagnostic, resulting in repeated scans or even call backs of the patients.
Accordingly, in institutions that deploy more than one image scanner, there is a need to harmonize imaging protocols across the scanners for the sake of uniformity and consistency. However, currently such harmonization can only be achieved, at best, semi-automatically. For example, on some conventional scanners, it is possible to manually export a protocol from one scanner and import on another or to transfer a protocol via Digital Imaging and Communications in Medicine (DICOM) transfer. The protocol must then be manually imported onto another scanner. Moreover, it is challenging to transfer protocols between individual scanners due to configuration differences that may exist between different scanners. For example, in the case of MRI, scanner differences can exist due to factors such as field strength and gradient performance. Although, it is possible to transfer a protocol from a scanner with one configuration to a scanner with a different configuration, the importing system is required to make changes to the protocol during the importing process based on certain heuristic rules which may introduce errors in the imported data.
Additionally, conventional techniques for storing imaging protocols are suboptimal. For example, imaging protocols are typically stored locally on the hard disk of the scanner, so in the event of a system crash, accidental deletion or modification, these protocols are irreversibly lost. While it is possible to create manual backups of the protocols at regular intervals, these backups are complete backups requiring large memory foot print and considerable amount of time to restore.
Accordingly, it is desired to provide an imaging protocol management system to allow for coordination, storage, and maintenance of imaging protocols across a group of image scanners.